February 2026 Summaries

In the context of AI applications, the choice between WebSockets and HTTP depends on the specific needs of the experience being developed. HTTP, known for its short-lived, request-response nature, is suitable for simple, stateless AI tasks such as single-shot queries and cached responses, while its streaming capabilities, though limited by half-duplex constraints, can handle basic token streaming. On the other hand, WebSockets offer persistent, bi-directional communication, making them ideal for complex, conversational AI applications that require continuous state management, real-time user interaction and steering, multi-device continuity, and collaborative environments. Modern AI frameworks often support both protocols, but the persistent connection of WebSockets is particularly advantageous for agentic workflows, where maintaining context and seamless interaction across devices is crucial. Companies like Ably AI Transport provide infrastructure solutions that address the complexities of deploying WebSocket-based AI applications, such as session continuity and multi-device synchronization, allowing developers to focus more on enhancing the AI experience itself.

Ably Pub/Sub has introduced a new feature that allows users to edit and delete previously published messages, addressing the challenge of maintaining consistency and coordination in real-time systems when messages need to be altered after delivery. This feature includes a clear model for versioning, history, and permission controls, ensuring that changes are reflected in real-time for subscribers and that the latest version of a message is always available in history queries. By keeping changes within the same channel stream, this update facilitates effective moderation and content removals, preventing outdated content from resurfacing during reconnects or refreshes. The system utilizes lexicographically sortable strings to manage message versions, allowing users to manage message updates and deletions seamlessly. This capability is particularly beneficial for applications requiring rapid content moderation, such as livestream chats and support workflows, where maintaining coherent and up-to-date transcripts is essential. The feature is currently in public preview and can be enabled through the Ably dashboard, with the potential to impact billing due to the persistence of messages on affected channels.

Ably AI Transport has introduced a feature called appends, designed to enhance the efficiency of streaming AI output by consolidating multiple token messages into a single, progressively growing message. This approach addresses delivery challenges, such as handling disconnections, refreshes, and late client joins, which can complicate message history and require additional engineering efforts for reconstruction. By appending tokens to an initial response message, appends simplify the processing of real-time and historical data, allowing for seamless reconnections and reducing the burden on client-side logic. This method also enables better management of token rates and message capacity, with options to adjust for responsiveness and efficiency. The new feature requires enabling specific channel rules and offers a streamlined alternative to building custom message reconstruction systems, making it advantageous for developers of agentic AI applications.